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app.R
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#
# This is a Shiny web application. You can run the application by clicking
# the 'Run App' button above.
#
# Find out more about building applications with Shiny here:
#
# http://shiny.rstudio.com/
#
library(shiny)
library(pxweb)
library(ggplot2)
library(tidyverse)
library(plotly)
library(ggthemes)
library(thematic)
library(scales)
library(shinydashboard)
library(geofi)
library(rjstat)
library(shinycssloaders)
library(stringr)
library(readr)
# Define UI for application that draws a histogram
ui <- fluidPage(
tags$style(type = "text/css", "html, body {width:100%;height:100%;background-color: #FAEBD7;}"),
tags$style(type = "text/css", ".info-box-text, .info-box-content p {font-family:Arial Narrow;font-size:5;}"),
tags$style(type = "text/css", ".sourceCite {font-family:Arial Narrow;font-size:5;text-align:right;font-style:italic;color:grey;}"),
tags$style(type = "text/css", ".kpiHeader {font-family:Arial Narrow;font-size:14;text-align:left;font-style:regular; }"),
tags$style(type = "text/css", ".pxwebcite {font-family:Arial Narrow;font-size:14;text-align:right;font-style:regular; }"),
theme = bslib::bs_theme(
base_font = bslib::font_google("Archivo Black")
),
fluidRow(
column(2,
plotOutput("finmapOutput", height = "150px")
),
column(8,
HTML("<h1 style='text-align:left;font-style:italic;'>Finland's Economy in Figures</h1>"),
HTML("<p style='text-align:left;font-style:italic;'>Dashboard in the spirit of Teollisuuden työnantajat TT's print publication from 1995</p>")
),
column(2)
),
fluidRow(
column(2,
HTML("<h6 style='text-align:center;'><i class='fas fa-industry'></i> GDP</h6>"),
hr(color="black"),
fluidRow(
infoBoxOutput ("gdpKPI", width = 6),
infoBoxOutput("gdpKPI2", width = 6)
),
span(div(textOutput("current_gdp_YearOutput"), class="kpiHeader"),
div(textOutput("cite_B1GMHOutput"), class = "sourceCite"))
),
column(2,
HTML("<h6 style='text-align:center;'><i class='fas fa-wallet'></i> INFLATION</h6>"),
hr(color="black"),
fluidRow(
infoBoxOutput("inflationKPI2", width = 4),
infoBoxOutput ("inflationKPI", width = 4),
infoBoxOutput("inflationKPI3", width = 4)
),
div(textOutput("current_infl_MonthOutput"), class="kpiHeader"),
div( textOutput("cite_unemployOutput"), class = "sourceCite")
),
column(3,
HTML("<h6 style='text-align:center;'><i class='fas fa-globe'></i> EXPORTS AND IMPORTS</h6>"),
hr(color="black"),
fluidRow(
infoBoxOutput ("exportKPI", width = 4),
infoBoxOutput("importKPI", width = 4),
infoBoxOutput("netexportKPI", width = 4)
),
div(textOutput("current_bop_MonthOutput"), class="kpiHeader"),
div( textOutput("cite_bopOutput"), class = "sourceCite")
),
column(3,
HTML("<h6 style='text-align:center;'><i class='fas fa-user'></i> LABOUR</h6>"),
hr(color="black"),
fluidRow(
infoBoxOutput("employmentKPI"),
infoBoxOutput("unemploymentKPI"),
infoBoxOutput("activityKPI")
),
div(textOutput("current_labour_MonthOutput"), class="kpiHeader"),
div( textOutput("cite_labourOutput"), class = "sourceCite")
),
column(2,
HTML("<h6 style='text-align:center;'><i class='fas fa-thin fa-virus'></i> COVID-19</h6>"),
hr(color="black"),
fluidRow(
infoBoxOutput("covidcaseKPI", width = 6),
infoBoxOutput("covidtestKPI", width = 6)
),
div(textOutput("current_covid_MonthOutput"), class="kpiHeader"),
div( textOutput("cite_covidOutput"), class = "sourceCite")
)
),
fluidRow(
#column(12, hr(color="black"))
),
fluidRow(
column(6,
fluidRow(
column(6,
HTML("<h6 style='text-align:center;'>GDP TREND</h6>"),
hr(color="black"),
plotOutput("gdpPlot", height = "300px") %>% withSpinner(color="black"),
div( textOutput("cite_B1GMHOutput2"), class = "sourceCite")
),
column(6,
HTML("<h6 style='text-align:center;'>GOVERNMENT DEBT & DEFICIT</h6>"),
hr(color="black"),
plotOutput("debtPlot", height = "300px") %>% withSpinner(color="black"),
div( textOutput("cite_debtOutput"), class = "sourceCite")
)
),
fluidRow(
column(4,
HTML("<h6 style='text-align:center;'>UNEMPLOYMENT RATE</h6>"),
hr(color="black"),
plotOutput("unemploymentPlot", height = "300px") %>% withSpinner(color="black"),
div( textOutput("cite_unemployOutput2"), class = "sourceCite")
),
column(4,
HTML("<h6 style='text-align:center;'>EXPORTS BY COUNTRY</h6>"),
hr(color="black"),
plotOutput("exportsByCountryPlot", height = "300px") %>% withSpinner(color="black"),
div( textOutput("cite_bopOutput2"), class = "sourceCite")
),
column(4,
HTML("<h6 style='text-align:center;'>EXPORTS BY PRODUCT</h6>"),
hr(color="black"),
plotOutput("exportsByIndustryPlot", height = "300px") %>% withSpinner(color="black"),
div( textOutput("cite_exportsByIndustry"), class = "sourceCite")
)
)
),
column(6,
HTML("<h6 style='text-align:center;'>INFLATION TREND BY PRODUCT</h6>"),
hr(color="black"),
plotOutput("hyodykePlot", height = "750px") %>% withSpinner(color="black"),
div( textOutput("cite_current_inflMonthOutput"), class = "sourceCite")
)
),
fluidRow(
column(12,
HTML("<div class='pxwebcite'>Sources:</div>"),
HTML("<div class='pxwebcite'>https://sampo.thl.fi/pivot/prod/fi/epirapo/covid19case/fact_epirapo_covid19case</div>"),
HTML("<div class='pxwebcite'>https://pxnet2.stat.fi/PXWeb/pxweb/fi/</div>"),
HTML("<div class='pxwebcite'>Mans Magnusson, Markus Kainu, Janne Huovari, and Leo Lahti (rOpenGov). pxweb: R tools for PXWEB API. URL: http://github.com/ropengov/pxweb</div>"),
HTML("<div class='pxwebcite'>Data is licensed under: Attribution 4.0 International (CC BY 4.0)</div>")
)
)
)
# Define server logic required to draw a histogram
server <- function(input, output) {
thematic_shiny(font = "auto")
# Helper to check if new data present ----------------
fShouldUpdate <- function(pxdataset) {
object = deparse(substitute(pxdataset))
Updated <- pxdataset[["metadata"]][[1]][["updated"]]
df.test <- as.data.frame(Updated)
df.old.value <- read_csv2(paste0(object, ".csv"))
if (df.test$Updated > df.old.value$Updated) {
write_csv2(df.test, paste0(object, ".csv"))
return(TRUE)
}
else
return(FALSE)
}
####################
### Unemployment ###
####################
pxweb_query_list.unemploy.test <- list("unit"=c("PC_ACT"), "geo"=c("FI"), "time"=c("2020"))
px_data.unemploy.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/Eurostat/tym/tps00203.px", query = pxweb_query_list.unemploy.test)
test.unemploy <- fShouldUpdate(px_data.unemploy.test)
if (test.unemploy == TRUE) {
pxweb_query_list.unemploy <- list("unit"=c("PC_ACT"), "geo"=c("EA19","EU27_2020","FI"), "time"=c("*"))
px_data.unemploy <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/Eurostat/tym/tps00203.px", query = pxweb_query_list.unemploy)
df.unemploy <- as.data.frame(px_data.unemploy, column.name.type = "text", variable.value.type = "text")
df.unemploy <- mutate(
df.unemploy,
Date = as.Date.character(paste(time, "-01", "-01", sep=""))
)
write_csv2(df.unemploy, "df.unemploy.csv")
}
else {
df.unemploy <- read_csv2("df.unemploy.csv")
}
cite.unemploy <- px_data.unemploy.test$metadata[[1]]$source
###########################
### Balance of Payments ###
###########################
pxweb_query_list.bop.test <- list("Kuukausi"=c("2021M12"), "Maksutase-er\U00E4"=c("CA"), "Tiedot"=c("C","D"))
px_data.bop.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/mata/kk/statfin_mata_pxt_12gf.px", query = pxweb_query_list.bop.test)
test.bop <- fShouldUpdate(px_data.bop.test)
if (test.bop == TRUE) {
pxweb_query_list.bop <- list("Kuukausi"=c("*"), "Maksutase-er\U00E4"=c("CA","GS","G","S","IN1","D1","D4P","D4O","IN2","KA"), "Tiedot"=c("C","D"))
px_data.bop <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/mata/kk/statfin_mata_pxt_12gf.px", query = pxweb_query_list.bop)
df.bop <- as.data.frame(px_data.bop, column.name.type = "text", variable.value.type = "text")
df.bop <- df.bop %>%
filter(
`BOP item` == "CA Current account"
) %>%
mutate(
Income = `Income, millions of euro`,
Expenditure = `Expenditure, millions of euro`,
Net = `Income, millions of euro` - `Expenditure, millions of euro`,
Date = as.Date.character(paste0(sub("M", "-", Month), "-01"))
)
write_csv2(df.bop, "df.bop.csv")
}
else {
df.bop <- read_csv2("df.bop.csv")
}
euro <- dollar_format(
prefix = "",
suffix = "\u20ac",
big.mark = ".",
decimal.mark = ","
)
current_bop <- df.bop %>%
filter(
Date == max(Date)
)
cite.bop <- px_data.bop.test$metadata[[1]]$source
###########################
### Exports by country ###
###########################
pxweb_query_list.exp_country.test <- list("Maksutase-er\U00E4"=c("GS"), "Maa"=c("EUR"), "Vuosinelj\U00E4nnes"=c("2021Q3"), "Tiedot"=c("C"))
px_data.exp_country.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/mata/nj/statfin_mata_pxt_12gg.px", query = pxweb_query_list.exp_country.test)
test.exp_country <- fShouldUpdate(px_data.exp_country.test)
if(test.exp_country == TRUE) {
pxweb_query_list.exp_country <- list("Maksutase-er\U00E4"=c("GS"), "Maa"=c("*"), "Vuosinelj\U00E4nnes"=c("*"), "Tiedot"=c("C"))
px_data.exp_country <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/mata/nj/statfin_mata_pxt_12gg.px", query = pxweb_query_list.exp_country)
df.exp_country <- as.data.frame(px_data.exp_country, column.name.type = "text", variable.value.type = "code")
df.exp_country <- df.exp_country %>%
mutate(
Year = substr(Quarter, 1, 4),
IsNumeric = as.integer(Country)
) %>%
filter(
Quarter == max(Quarter)
)
df.exp_country <- df.exp_country %>%
filter(
df.exp_country$IsNumeric != "NA"
)
df.exp_country <- top_n(df.exp_country, n = 10, wt = df.exp_country$`Income, millions of euro`)
df.exp_country <- df.exp_country %>%
inner_join(as.data.frame(px_data.exp_country$pxweb_metadata[[2]][[2]]), by = c("Country" = "values"))
write_csv2(df.exp_country, "df.exp_country.csv")
}
else {
df.exp_country <- read_csv2("df.exp_country.csv")
}
cite.exp_country <- px_data.exp_country.test$metadata[[1]]$source
###################################
### Exports: Goods vs. Services ###
###################################
pxweb_query_list.exportBranch.test <- list("Palveluer\U00E4"=c("G"), "Alue"=c("ULK"), "Vuosinelj\U00E4nnes"=c("2021Q3"), "Tiedot"=c("C"))
px_data.exportBranch.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/tpulk/statfin_tpulk_pxt_12gq.px", query = pxweb_query_list.exportBranch.test)
test.exportBranch <- fShouldUpdate(px_data.exportBranch.test)
if(test.exportBranch == TRUE) {
pxweb_query_list.exportBranch <- list("Palveluer\U00E4"=c("*"), "Alue"=c("ULK"), "Vuosinelj\U00E4nnes"=c("*"), "Tiedot"=c("C","D"))
px_data.exportBranch <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/tpulk/statfin_tpulk_pxt_12gq.px", query = pxweb_query_list.exportBranch)
df.exportBranch <- as.data.frame(px_data.exportBranch, column.name.type = "text", variable.value.type = "text") %>%
mutate(
code = trimws(substr(`Service item`, 1, str_locate(`Service item`, " "))),
item = trimws(substr(`Service item`, str_locate(`Service item`, " "), length(`Service item`))),
Year = substr(Quarter, 1, 4),
) %>%
filter(
code %in% c("G", "S")
)
write_csv2(df.exportBranch, "df.exportBranch.csv")
}
else {
df.exportBranch <- read_csv2("df.exportBranch.csv")
}
cite.exportBranch <- px_data.exportBranch.test$metadata[[1]]$source
################
### S13 Debt ###
################
pxweb_query_list.debt.test <- list("Vuosi"=c("2018"), "Sektori"=c("S13"), "Tiedot"=c("*"))
px_data.debt.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/jul/jali/statfin_jali_pxt_122g.px", query = pxweb_query_list.debt.test)
test.px_data.debt <- fShouldUpdate(px_data.debt.test)
if (test.px_data.debt == TRUE) {
pxweb_query_list.debt <- list("Vuosi"=c("*"), "Sektori"=c("*"), "Tiedot"=c("*"))
px_data.debt <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/jul/jali/statfin_jali_pxt_122g.px", query = pxweb_query_list.debt)
df.debt <- as.data.frame(px_data.debt, column.name.type = "text", variable.value.type = "text") %>%
filter(
Sector == "S13 General government"
) %>%
mutate(
Date = as.Date.character(paste0( substr(Year, 1, 4), "-01", "-01"))
)
write_csv2(df.debt, "df.debt.csv")
}
else {
df.debt <- read_csv2("df.debt.csv")
}
cite.debt = px_data.debt.test$metadata[[1]]$source
#################
### GDP B1GMH ###
#################
pxweb_query_list.B1GMH2.test <- list("Taloustoimi"=c("B1GMH"), "Vuosi"=c("2019"), "Tiedot"=c("cp"))
px_data.B1GMH2.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/vtp/statfin_vtp_pxt_11sf.px", query = pxweb_query_list.B1GMH2.test)
test.px_data.B1GMH <- fShouldUpdate(px_data.B1GMH2.test)
if (test.px_data.B1GMH == TRUE) {
pxweb_query_list.B1GMH2 <- list("Taloustoimi"=c("B1GMH"), "Vuosi"=c("*"), "Tiedot"=c("*"))
px_data.B1GMH2 <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/kan/vtp/statfin_vtp_pxt_11sf.px", query = pxweb_query_list.B1GMH2)
df.B1GMH2 <- as.data.frame(px_data.B1GMH2, column.name.type = "text", variable.value.type = "text")
df.B1GMH2 <- df.B1GMH2 %>%
mutate(
Date = as.Date.character(paste0( substr(Year, 1, 4), "-01", "-01"))
)
write_csv2(df.B1GMH2, "df.B1GMH2.csv")
}
else {
df.B1GMH2 <- read_csv2("df.B1GMH2.csv")
}
current_gdp <- df.B1GMH2 %>%
filter(
Date == max(Date)
)
cite.B1GMH2 <- px_data.B1GMH2.test$metadata[[1]]$source
#################
### Inflation ###
#################
pxweb_query_list.test <- list("Kuukausi"=c("*"), "Tiedot"=c("*"))
Hyodyke.test <- paste0("Hy", "\U00F6", "dyke")
pxweb_query_list.test[[Hyodyke.test]] <- c("0")
px_data.inflation.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/hin/khi/kk/statfin_khi_pxt_11xd.px", query = pxweb_query_list.test)
test.inflation <- fShouldUpdate(px_data.inflation.test)
if (test.inflation == TRUE) {
pxweb_query_list <- list("Kuukausi"=c("*"), "Tiedot"=c("*"))
# UTF-8 conversion for scandics
Hyodyke <- paste("Hy", "\U00F6", "dyke", sep = "")
pxweb_query_list[[Hyodyke]] <- c("*")
px_data <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/hin/khi/kk/statfin_khi_pxt_11xd.px", query = pxweb_query_list)
px.df <- as.data.frame(px_data, column.name.type = "text", variable.value.type = "text")
px.df <- rename(px.df, Hyodyke_new = Commodity)
px.df <- px.df %>%
mutate(
Date = as.Date.character(paste(sub("M", "-", Month), "-01", sep = ""))
) %>%
filter(
!grepl("\\.", Hyodyke_new)
)
write_csv2(px.df, "df.inflation.csv")
}
else {
px.df <- read_csv2("df.inflation.csv")
}
cite <- paste("Source:", px_data.inflation.test$metadata[[1]]$source)
current_infl <- px.df %>%
filter(
Month == max(Month) & Hyodyke_new == "0 CONSUMER PRICE INDEX"
)
px.df <- px.df %>%
filter(
Hyodyke_new != "0 CONSUMER PRICE INDEX" & !is.na(`Annual change (%)`)
)
prods <- as.factor(px.df$Hyodyke_new)
title <- paste("Inflation by product", sep = "")
ytitle <- paste("Hy", "\U00F6", "dykkeet", sep = "")
cite.infl <- px_data.inflation.test$metadata[[1]]$source
############
## LABOUR ##
############
pxweb_query_list.labour.test <- list("Vuosi"=c("2021"), "Sukupuoli"=c("SSS"), "Suuralue 2012"=c("SSS"), "Tiedot"=c("Vaesto","Tyovoima","Tyolliset","Tyottomat","Tyov_kuulumattomat","tyovoimaosuus","Tyollisyysaste_15_64","Tyottomyysaste"))
px_data.labour.test <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/tym/tyti/vv/statfin_tyti_pxt_13ak.px", query = pxweb_query_list.labour.test)
test.labour <- fShouldUpdate(px_data.labour.test)
if(test.labour) {
pxweb_query_list.labour <- list("Vuosi"=c("*"), "Sukupuoli"=c("SSS"), "Suuralue 2012"=c("SSS"), "Tiedot"=c("Vaesto","Tyovoima","Tyolliset","Tyottomat","Tyov_kuulumattomat","tyovoimaosuus","Tyollisyysaste_15_64","Tyottomyysaste"))
px_data.labour <- pxweb_get(url = "https://pxnet2.stat.fi/PXWeb/api/v1/en/StatFin/tym/tyti/vv/statfin_tyti_pxt_13ak.px", query = pxweb_query_list.labour)
df.labour <- as.data.frame(px_data.labour, column.name.type = "text", variable.value.type = "text")
df.labour <- df.labour %>%
filter(
df.labour$Year == max(Year)
)
write_csv2(df.labour, "df.labour.csv")
}
else {
df.labour <- read_csv2("df.labour.csv")
}
cite.labour <- px_data.labour.test$metadata[[1]]$source
############
## COVID ##
############
url_base <- "https://sampo.thl.fi/pivot/prod/fi/epirapo/covid19case/fact_epirapo_covid19case.json"
#request <- "?row=dateweek20200101-509030&row=hcdmunicipality2020-445222&column=measure-444833.445356.492118.445344.&fo=1&row=445268L"
request <- "?row=dateweek20200101-509030&column=measure-444833.445356.492118.445344.&fo=1"
url <- paste0(url_base, request)
cube <- fromJSONstat(url, naming = "label", use_factors = F, silent = T)
res <- cube[[1]]
df.covid <- res %>%
filter(
res$dateweek20200101 == max(res$dateweek20200101)
#res$dateweek20200101 == max(res$dateweek20200101) & trimws(res$hcdmunicipality2020) == "Kaikki Alueet" & trimws(res$hcdmunicipality20201) == "Yhteens\U00E4"
) %>%
group_by(
dateweek20200101,
measure
)
cases <- paste0("Tapausten lukum", "\U00E4\U00E4r\U00E4")
tests <- paste0("Testausm", "\U00E4\U00E4r\U00E4")
df.covid.cases <- df.covid %>%
filter(
trimws(measure) == cases
)
df.covid.tests <- df.covid %>%
filter(
measure == tests
)
#########
## MAP ##
#########
finmap <- get_municipalities(year = 2020)
finmap <- finmap %>%
transmute(
geom = finmap$geom,
vuosi = finmap$vuosi
)
###################################################################################################
########### OUTPUTS ###########
###################################################################################################
output$hyodykePlot <- renderPlot({
ggplot(px.df, aes(Date, px.df$`Annual change (%)`)) +
geom_area(alpha = 0.5) +
geom_point(size=1, colour="black", alpha=0.5) +
geom_smooth(na.rm = TRUE, color="black", span=1.0) +
facet_wrap(~Hyodyke_new, ncol = 3) +
theme_void() +
theme(
legend.position = "none",
panel.border = element_rect(colour = "grey70", fill = NA),
panel.grid.major = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
title = element_text(face = "italic"),
axis.text.x = element_text(
size = 12,
hjust = 1
),
axis.text.y = element_text(
vjust = 0.5,
size = 12
)
) +
scale_y_continuous(expand = c(0,0), labels = scales::number_format(accuracy = 1, suffix = " %")) +
scale_x_date(expand = c(0,0)) +
ylab(ytitle)
})
output$gdpPlot <- renderPlot({
ggplot(df.B1GMH2, aes(Date, `Volume series, reference yea 2020`)) +
geom_area(alpha = 0.5) +
geom_point(size=2, colour="black", alpha=0.5) +
geom_text(
aes(y = df.B1GMH2$`Volume series, reference yea 2020`),
vjust = -1,
size = 3,
check_overlap = T,
label = round(df.B1GMH2$`Volume series, reference yea 2020` / 1000, 0)
) +
theme_void() +
ggtitle("GDP volume, reference year 2020") +
theme(
plot.title = element_text(
vjust = 0.7,
hjust = 0.1
),
panel.grid.major = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
axis.text.x = element_text(
angle = 45,
size = 12,
hjust = 1
),
axis.text.y = element_text(
vjust = 1,
size = 12
)
) +
coord_cartesian(clip = "on") +
scale_y_continuous(expand = c(0.1,0.1), limits = c(0, 300000), labels = scales::number_format(big.mark = " ", accuracy = 1, suffix = " M\U20ac")) +
scale_x_date(expand = c(0,0))
})
output$unemploymentPlot <- renderPlot({
ggplot(df.unemploy, aes(df.unemploy$Date, df.unemploy$`Total unemployment rate`, shape=factor(df.unemploy$geo) )) +
geom_line() +
geom_point(color="black", fill="grey70", size=4) +
theme_void() +
theme(
legend.position = c(0.025, 0.4),
legend.justification = c(0, 1),
legend.direction = "vertical",
legend.title = element_blank(),
panel.grid.major = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
title = element_text(face = "italic"),
axis.text.x = element_text(
size = 12,
angle = 45,
hjust = 1
),
axis.text.y = element_text(
vjust = 1,
size = 12
)
) +
scale_color_manual(values = c("black", "grey20", "grey80")) +
scale_fill_grey() +
scale_y_continuous(expand = c(0.1,0.1), limits = c(0, 15), labels = scales::number_format(accuracy = 1, suffix = " %")) +
scale_x_date(expand = c(0,0))
})
output$exportsByCountryPlot <- renderPlot({
ggplot(df.exp_country, aes(x = reorder(df.exp_country$valueTexts, df.exp_country$`Income, millions of euro` ), y = df.exp_country$`Income, millions of euro`)) +
geom_col() +
geom_text(
label = df.exp_country$`Income, millions of euro`,
size = 3,
check_overlap = TRUE,
position = position_stack(vjust = 0.5),
color = "white"
) +
theme_void() +
coord_flip() +
ggtitle(df.exp_country$Quarter) +
theme(
plot.title = element_text(
vjust = 0.7,
hjust = 0.1
),
#legend.title = element_blank(),
panel.grid.major.x = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
#title = element_text(face = "italic"),
axis.text.x = element_text(
vjust = 0.5,
angle = 45,
size = 12
),
axis.text.y = element_text(
vjust = 0.5,
size = 12
)
) +
scale_y_continuous(expand = c(0,0), labels = scales::number_format(big.mark = " ", accuracy = 1, suffix = " M\U20ac"))
})
output$exportsByIndustryPlot <- renderPlot({
ggplot(df.exportBranch, aes(x = Year, y=df.exportBranch$`Export, millions of euro`, fill = df.exportBranch$item, color = df.exportBranch$item)) +
geom_bar(position="dodge", stat="identity") +
theme_void() +
scale_color_grey() +
theme(
legend.position = c(0.025, 0.975),
legend.justification = c(0, 1),
legend.direction = "horizontal",
legend.title = element_blank(),
panel.grid.major = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
title = element_text(face = "italic"),
axis.text.x = element_text(
vjust = 0.5,
angle = 45,
size = 12
),
axis.text.y = element_text(
vjust = 1,
size = 12
)
) +
scale_y_continuous(expand = c(0,0), labels = scales::number_format(big.mark = " ", accuracy = 1, suffix = " M\U20ac")) +
scale_fill_grey()
})
output$debtPlot <- renderPlot({
ggplot(df.debt, aes(x=Date)) +
geom_bar(aes(y = df.debt$`EDP deficit (-) / EDP surplus (+), millions of euro`), stat="identity", fill="grey70", color="black", alpha=0.5) +
geom_line(aes(y = df.debt$`EDP debt, ratio to GDP, %`*100, group = 1)) +
geom_point(aes(y = df.debt$`EDP debt, ratio to GDP, %`*100)) +
scale_y_continuous(
expand = c(0,0),
labels = scales::number_format(big.mark = " ", accuracy = 1, suffix = " M\U20ac"),
name = "Deficit",
sec.axis = sec_axis(~./100, name = "Debt % of GDP", labels = scales::number_format(big.mark = " ", accuracy = 1, suffix = " %"))
) +
geom_text(
aes(y = df.debt$`EDP debt, ratio to GDP, %`*100),
vjust = -1,
size = 3,
label = df.debt$`EDP debt, ratio to GDP, %`,
check_overlap = T,
) +
theme_void() +
theme(
legend.position = c(0.025, 0.975),
legend.justification = c(0, 1),
legend.direction = "horizontal",
#legend.title = element_blank(),
panel.grid.major = element_line(colour = "grey70"),
strip.text = element_text(size = 12),
title = element_text(face = "italic"),
axis.text.x = element_text(
vjust = 0.5,
angle = 45,
size = 12
),
axis.text.y = element_text(
size = 12
),
axis.title.y = element_text(
size = 12,
angle = 90,
hjust = 1
)
)
})
output$finmapOutput <- renderPlot({
plot(finmap, border = NA, col="black", main = NULL)
})
output$gdpKPI <- renderInfoBox({
infoBox("", paste(format(round(current_gdp$`Current prices, millions of euro`, 0), big.mark = " "), " M\U20ac"), subtitle = "Current prices")
})
output$gdpKPI2 <- renderInfoBox({
infoBox("", paste(current_gdp$`Changes in volume, %`, "%"), subtitle = "Annual change in volume")
})
output$inflationKPI <- renderInfoBox({
infoBox("", current_infl$`Point figure`, subtitle = "Index")
})
output$inflationKPI2 <- renderInfoBox({
infoBox("", paste(current_infl$`Annual change (%)`, "%"), subtitle = "Annual change")
})
output$inflationKPI3 <- renderInfoBox({
infoBox("", paste(current_infl$`Monthly change (%)`, "%"), subtitle = "Monthly change")
})
output$exportKPI <- renderInfoBox({
infoBox("", paste(format(current_bop$`Income, millions of euro`, big.mark = " "), "M\U20ac"), subtitle = "Exports")
})
output$importKPI <- renderInfoBox({
infoBox("", paste(format(current_bop$`Expenditure, millions of euro`, big.mark = " "), "M\U20ac"), subtitle = "Imports")
})
output$netexportKPI <- renderInfoBox({
infoBox("", paste(format(current_bop$Net, big.mark = " "), "M\U20ac"), subtitle = "Net exports")
})
output$covidcaseKPI <- renderInfoBox({
infoBox("", format( as.integer(df.covid.cases$value), big.mark = " "), subtitle = "Cases")
})
output$covidtestKPI <- renderInfoBox({
infoBox("", format(as.integer(df.covid.tests$value), 0, big.mark = " "), subtitle = "Tests")
})
output$employmentKPI <- renderInfoBox({
infoBox("", paste(df.labour$`Employment rate, persons aged 15-64, %`, "%"), subtitle = "Employment rate")
})
output$unemploymentKPI <- renderInfoBox({
infoBox("", paste(df.labour$`Unemployment rate, %`, "%"), subtitle = "Unemployment rate")
})
output$activityKPI <- renderInfoBox({
infoBox("", paste(df.labour$`Activity rate, %`, "%"), subtitle = "Activity rate")
})
output$current_gdp_YearOutput <- renderText({current_gdp$Year})
output$cite_B1GMHOutput <- renderText({cite.B1GMH2})
output$cite_B1GMHOutput2 <- renderText({cite.B1GMH2})
output$current_infl_MonthOutput <- renderText({current_infl$Month})
output$cite_current_inflMonthOutput <- renderText({cite.infl})
output$cite_unemployOutput <- renderText({cite.unemploy})
output$cite_unemployOutput2 <- renderText({cite.unemploy})
output$current_covid_MonthOutput <- renderText({df.covid.cases$dateweek20200101})
output$cite_covidOutput <- renderText({ "Finnish National Infectious Diseases Register" })
output$current_bop_MonthOutput <- renderText({ current_bop$Month })
output$cite_bopOutput <- renderText({cite.bop})
output$cite_bopOutput2 <- renderText({cite.bop})
output$cite_exportsByIndustry <- renderText({cite.exportBranch})
output$cite_debtOutput <- renderText({cite.debt})
output$current_labour_MonthOutput <- renderText({ df.labour$Year })
output$cite_labourOutput <- renderText({cite.labour})
}
# Run the application
shinyApp(ui = ui, server = server)